Self Learning Control System and Method for Optimizing a Consumable Input Variable

ABSTRACT

A control system for an operable system such as a flow control system or temperature control system. The system operates in a control loop to regularly update a model with respect at least one optimizable input variable based on the detected variables. The model provides prediction of use of the input variables in all possible operation points or paths of the system variables which achieve an output setpoint. In some example embodiments, the control loop is performed during initial setup and subsequent operation of the one or more operable elements in the operable system. The control system is self-learning in that at least some of the initial and subsequent parameters of the system are determined automatically during runtime.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application under 35 U.S.C. §111(a)of U.S. patent application Ser. No. 14/443,207, which application is aNational Stage Application entered May 15, 2015 under 35 U.S.C. §371 ofPCT/CA2013/050868 filed Nov. 13, 2013, which application claims thebenefit of priority to U.S. Provisional Patent Application No.61/736,051 filed Dec. 12, 2012 and to U.S. Provisional PatentApplication No. 61/753,549 filed Jan. 17, 2013, all of whichapplications are herein incorporated by reference in their entirety intothe Detailed Description of Example Embodiments, herein below.

TECHNICAL FIELD

Some example embodiments relate to control systems, and some exampleembodiments relate specifically to flow control systems or temperaturecontrol systems.

BACKGROUND

Systems with more degrees of freedom than restrictions and goals can beoperated in many different ways while still achieving the same statedgoals. A typical example is a car which can be driven between two pointsthrough different routes, at different speeds, in different gears andusing the breaks differently.

If how these systems perform on non-stated goals is analyzed, usuallyroom for improvement is found. For instance, most cars are neitheroperated using the minimum possible amount of gas, nor wearing them aslittle as possible, nor achieving the minimum transit time legally andsafely possible.

Once an optimal system is designed for a given environment, it is oftenthe case where the environment itself changes the system no longeroptimizes its originally designed function.

Additional difficulties with existing systems may be appreciated in viewof the description below.

SUMMARY

In accordance with some aspects, there is provided a control system fortemperature control systems and circulating devices such as pumps,boosters and fans, centrifugal machines, and related systems.

In one aspect, there is provided a control system for controlling anoperable system, comprising: one or more operable elements resulting inoutput variables, wherein there is more than one operation point or pathof system variables of the operable system that can provide a givenoutput setpoint, wherein at least one system variable at an operationpoint or path restricts operation of another system variable at theoperation point or path; and one or more controllers configured tooperate in a control loop to: detect input variables including one ormore optimizable input variables which are required to determine theoutput variables, detect the system variables, update a model withrespect to the at least one optimizable input variable based on thedetected input variables and the detected system variables, the modelproviding prediction of use of the input variables in all possibleoperation points or paths of the system variables which achieve anoutput setpoint, and operate, based on one or more of the detected inputvariables and the detected system variables, the one or more operableelements in accordance with the optimized model to provide an optimaloperation point or path of the system variables which achieves theoutput setpoint which optimizes use of the at least one optimizableinput variable.

In another aspect, there is provided a flow control system forcontrolling a flow system, comprising: a circulating pump having avariably controllable motor resulting in output variables includingpressure and flow for the flow system; and one or more controllersconfigured to operate in a control loop to: detect input variablesincluding one or more optimizable input variables which are required todetermine the output variables, detect the output variables, update amodel with respect to the at least one optimizable input variable basedon the detected input variables and the detected output variables, themodel providing prediction of use of the input variables in all possibleoperation points or paths of the output variables which achieve anoutput setpoint, optimize a control curve in accordance with the modelwith respect to the at least one optimizable input variable based on thedetected input variables and the detected output variables, the controlcurve providing co-ordination of the operation point of the pressure andflow in order to achieve the output setpoint, and operate, based on oneor more of the detected variables, the variably controllable motor inaccordance with the optimized control curve to provide the operationpoint of the pressure and flow to achieve the output setpoint.

In another aspect, there is provided a method system for controlling anoperable system, the operable system including one or more operableelements resulting in output variables, wherein there is more than oneoperation point or path of system variables of the operable system thatcan provide a given output setpoint, wherein at least one systemvariable at an operation point or path restricts operation of anothersystem variable at the operation point or path, the method beingperformed as a control loop and comprising: detecting input variablesincluding one or more optimizable input variables which are required todetermine the output variables; detecting the system variables; updatinga model with respect to the at least one optimizable input variablebased on the detected input variables and the detected system variables,the model providing prediction of use of the input variables in allpossible operation points or paths of the system variables which achievean output setpoint; and operating, based on one or more of the detectedinput variables and the detected system variables, the one or moreoperable elements in accordance with the optimized model to provide anoptimal operation point or path of the system variables which achievesthe output setpoint which optimizes use of the at least one optimizableinput variable.

In another aspect, there is provided a non-transitory computer readablemedium comprising instructions which, when executed by one or morecontrollers, cause the controllers to control an operable system in acontrol loop, the operable system including one or more operableelements resulting in output variables, wherein there is more than oneoperation point or path of system variables of the operable system thatcan provide a given output setpoint, wherein at least one systemvariable at an operation point or path restricts operation of anothersystem variable at the operation point or path, the instructionscomprising: instructions for detecting input variables including one ormore optimizable input variables which are required to determine theoutput variables; instructions for detecting the system variables;instructions for updating a model with respect to the at least oneoptimizable input variable based on at least one of the detected inputvariables and the detected system variables, the model providingprediction of use of the input variables in all possible operationpoints or paths of the system variables which achieve an outputsetpoint; and instructions for operating, based on one or more of thedetected input variables and the detected system variables, the one ormore operable elements in accordance with the optimized model to providean optimal operation point or path of the system variables whichachieves the output setpoint which optimizes use of the at least oneoptimizable input variable.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will now be described, by way of example only, withreference to the attached Figures, wherein:

FIG. 1 illustrates an example block diagram of a circulating systemhaving intelligent variable speed control pumps, to which exampleembodiments may be applied;

FIG. 2 illustrates an example operation graph of a variable speedcontrol pump;

FIG. 3 shows a diagram illustrating internal sensing control of avariable speed control pump;

FIG. 4 illustrates an example load profile for a system such as abuilding;

FIG. 5 illustrates an example detailed block diagram of a controldevice, in accordance with an example embodiment;

FIG. 6 illustrates a control system for co-ordinating control ofdevices, in accordance with an example embodiment;

FIG. 7 illustrates another control system for co-ordinating control ofdevices, in accordance with another example embodiment;

FIG. 8 illustrates a flow diagram of an example method for co-ordinatingcontrol of devices, in accordance with an example embodiment;

FIG. 9 illustrates an example operation graph of a variable speedcontrol pump, having an adjustable control curve which uses detectedsystem hydraulic resistance for energy consumption optimization, inaccordance with an example embodiment;

FIGS. 10A, 10B and 10C illustrate example flow diagrams for adjustingthe operation graph of FIG. 9, in accordance with example embodiments;

FIG. 11 illustrates an example adjustable load profile for a system,which can be used to adjust a control curve of FIG. 2, in accordancewith another example embodiment;

FIG. 12 illustrates an example block diagram of a circulating systemhaving external sensors, in accordance with an example embodiment; and

FIG. 13 illustrates an example flow control system for a flow system, inaccordance with an example embodiment.

Like reference numerals may be used throughout the Figures to denotesimilar elements and features.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

At least some example embodiments generally provide an automated controlsystem for temperature control systems and circulating devices such aspumps, boosters and fans, centrifugal machines, and related systems.

In some example embodiments, there is provided a control system for anoperable system such as a flow control system or temperature controlsystem. Example embodiments relate to “processes” in the industrialsense, meaning a process that outputs product(s) (e.g. hot water, air)using inputs (e.g. cold water, fuel, air, etc.). The system operates ina control loop to regularly optimize a model with respect at least oneoptimizable input variable based on the detected variables. The modelprovides prediction of input variable use in all possible operationpoints or paths of the system variables which achieve an outputsetpoint. In some example embodiments, the control loop is performedduring initial setup and subsequent operation of the one or moreoperable elements in the operable system. The control system isself-learning in that at least some of the initial and subsequentparameters of the system are determined automatically during runtime,i.e., would not require manual configuration.

In pumping systems where the flow demand changes over time there areseveral conventional procedures to adapt the operation of the pump(s) tosatisfy such demand without exceeding the pressure rating of the system,burning seals or creating vibration, and they may also attempt tooptimize the energy use.

Traditional systems have used one or several constant speed pumps andattempted to maintain the discharge pressure (local or remote) constant,when the flow demand changed, by changing the number of running pumpsand/or by operating pressure reducing, bypass and discharge valves.

One popular system in use today has several pumps; each equipped with anelectronic variable speed drive, and operates them to control one ormore pressure(s) remotely in the system, measured by remote sensors(usually installed at the furthest location served or ⅔ down the line).At the remote sensor location(s) a minimum pressure has to bemaintained, so the deviation of the measured pressure(s) with respect tothe target(s) is calculated. The speed of the running pumps is thenadjusted (up or down) to the lowest that maintains all the measuredpressures at or above their targets. When the speed of the running pumpsexceeds a certain value (usually 95% of the maximum speed), another pumpis started. When the speed falls below a certain value (50% or higher,and sometimes dependent on the number of pumps running), a pump isstopped. This sequencing method is designed to minimize the number ofpumps used to provide the required amount of flow.

An alternative to this type of system measures the flow and pressure atthe pump(s) and estimates the remote pressure by calculating thepressure drop in the pipes in between. The pump(s) are then controlledas per the procedure described above, but using the estimated remotepressure instead of direct measurements. This alternative saves the costof the remote sensor(s), plus their wiring and installation, butrequires a local pressure sensor and flow meter.

One type of pump device estimates the local flow and/or pressure fromthe electrical variables provided by the electronic variable speeddrive. This technology is typically referred to in the art as“sensorless”. Example implementations using a single pump are describedin PCT Patent Application Publication No. WO 2005/064167 to Witzel etal., U.S. Pat. No. 7,945,411 to Kernan et al., U.S. Pat. No. 6,592,340to Horo et al. and DE Pat. No. 19618462 to Foley. The single device canthen be controlled, but using the estimated local pressure and flow tothen infer the remote pressure, instead of direct fluid measurements.This method saves the cost of sensors and their wiring and installation,however, these references may be limited to the use of a single pump.

In one example embodiment, there is provided a control system forsourcing a load, including: a plurality of sensorless circulatingdevices each including a respective circulating operable elementarranged to source the load, each device configured to self-detect powerand speed of the respective device; and one or more controllersconfigured to: correlate, for each device, the detected power and speedto one or more output properties including pressure and flow, andco-ordinate control of each of the devices to operate at least therespective circulating operable element to co-ordinate one or moreoutput properties to achieve a pressure setpoint at the load.

Reference is first made to FIG. 1 which shows in block diagram form acirculating system 100 having intelligent variable speed circulatingdevices such as control pumps 102 a, 102 b (each or individuallyreferred to as 102), to which example embodiments may be applied. Thecirculating system 100 may relate to a building 104 (as shown), a campus(multiple buildings), vehicle, plant, generator, heat exchanger, orother suitable infrastructure or load. Each control pump 102 may includeone or more respective pump devices 106 a, 106 b (each or individuallyreferred to as 106) and a control device 108 a, 108 b (each orindividually referred to as 108) for controlling operation of each pumpdevice 106. The particular circulating medium may vary depending on theparticular application, and may for example include glycol, water, air,fuel, and the like.

As illustrated in FIG. 1, the circulating system 100 may include one ormore loads 110 a, 110 b, 110 c, 110 d, wherein each load may be avarying usage requirement based on HVAC, plumbing, etc. Each 2-way valve112 a, 112 b, 112 c, 112 d may be used to manage the flow rate to eachrespective load 110 a, 110 b, 110 c, 110 d. As the differential pressureacross the load decreases, the control device 108 responds to thischange by increasing the pump speed of the pump device 106 to maintainor achieve the pressure setpoint. If the differential pressure acrossthe load increases, the control device 108 responds to this change bydecreasing the pump speed of the pump device 106 to maintain or achievethe pressure setpoint. In some example embodiments, the control valves112 a, 112 b, 112 c, 112 d can include faucets or taps for controllingflow to plumbing systems. In some example embodiments, the pressuresetpoint can be fixed, continually or periodically calculated,externally determined, or otherwise specified.

The control device 108 for each control pump 102 may include an internaldetector or sensor, typically referred to in the art as a “sensorless”control pump because an external sensor is not required. The internaldetector may be configured to self-detect, for example, deviceproperties such as the power and speed of the pump device 106. Otherinput variables may be detected. The pump speed of the pump device 106may be varied to achieve a pressure and flow setpoint of the pump device106 in dependence of the internal detector. A program map may be used bythe control device 108 to map a detected power and speed to resultantoutput properties, such as head output and flow output (H, F).

Referring still to FIG. 1, the output properties of each control device102 are controlled to, for example, achieve a pressure setpoint at thecombined output properties 114, shown at a load point of the building104. The output properties 114 represent the aggregate or total of theindividual output properties of all of the control pumps 102 at theload, in this case, flow and pressure. In typical conventional systems,an external sensor (not shown) would be placed at the location of theoutput properties 114 and associated controls (not shown) would be usedto control or vary the pump speed of the pump device 106 to achieve apressure setpoint in dependence of the detected flow by the externalsensor. In contrast, in example embodiments the output properties 114are instead inferred or correlated from the self-detected deviceproperties, such as the power and speed of the pump devices 106, and/orother input variables. As shown, the output properties 114 are locatedat the most extreme load position at the height of the building 104 (orend of the line), and in other example embodiments may be located inother positions such as the middle of the building 104, ⅔ from the topof the building 104 or down the line, or at the farthest building of acampus.

One or more controllers 116 (e.g. processors) may be used to co-ordinatethe output flow of the control pumps 102. As shown, the control pumps102 may be arranged in parallel with respect to the shared loads 110 a,110 b, 110 c, 110 d. For example, the individual output properties ofeach of the control pumps 102 can be inferred and controlled by thecontroller 116 so as to achieve the aggregate output properties 114.This feature is described in greater detail below.

In some examples, the circulating system 100 may be a chilledcirculating system (“chiller plant”). The chiller plant may include aninterface 118 in thermal communication with a secondary circulatingsystem. The control valves 112 a, 112 b, 112 c, 112 d manage the flowrate to the cooling coils (e.g., load 110 a, 110 b, 110 c, 110 d). Each2-way valve 112 a, 112 b, 112 c, 112 d may be used to manage the flowrate to each respective load 110 a, 110 b, 110 c, 110 d. As a valve 112a, 112 b, 112 c, 112 d opens, the differential pressure across the valvedecreases. The control device 108 responds to this change by increasingthe pump speed of the pump device 106 to achieve a specified outputsetpoint. If a control valve 112 a, 112 b, 112 c, 112 d closes, thedifferential pressure across the valve increases, and the controldevices 108 respond to this change by decreasing the pump speed of thepump device 106 to achieve a specified output setpoint.

In some other examples, the circulating system 100 may be a heatingcirculating system (“heating plant”). The heater plant may include aninterface 118 in thermal communication with a secondary circulatingsystem. In such examples, the control valves 112 a, 112 b, 112 c, 112 dmanage the flow rate to heating elements (e.g., load 110 a, 110 b, 110c, 110 d). The control devices 108 respond to changes in the heatingelements by increasing or decreasing the pump speed of the pump device106 to achieve the specified output setpoint.

Referring still to FIG. 1, the pump device 106 may take on various formsof pumps which have variable speed control. In some example embodiments,the pump device 106 includes at least a sealed casing which houses thepump device 106, which at least defines an input element for receiving acirculating medium and an output element for outputting the circulatingmedium. The pump device 106 includes one or more operable elements,including a variable motor which can be variably controlled from thecontrol device 108 to rotate at variable speeds. The pump device 106also includes an impeller which is operably coupled to the motor andspins based on the speed of the motor, to circulate the circulatingmedium. The pump device 106 may further include additional suitableoperable elements or features, depending on the type of pump device 106.Device properties of the pump device 106, including the motor speed andpower, may be self-detected by the control device 108.

Reference is now made to FIG. 2, which illustrates a graph 200 showingan example suitable range of operation 202 for a variable speed device,in this example the control pump 102. The range of operation 202 isillustrated as a polygon-shaped region or area on the graph 200, whereinthe region is bounded by a border represents a suitable range ofoperation. For example, a design point may be, e.g., a maximum expectedsystem load as in point A (210) as required by a system such as abuilding 104 at the output properties 114 (FIG. 1).

The design point, Point A (210), can be estimated by the system designerbased on the flow that will be required by a system for effectiveoperation and the head/pressure loss required to pump the design flowthrough the system piping and fittings. Note that, as pump headestimates may be over-estimated, most systems will never reach thedesign pressure and will exceed the design flow and power. Othersystems, where designers have under-estimated the required head, willoperate at a higher pressure than the design point. For such acircumstance, one feature of properly selecting one or more intelligentvariable speed pumps is that it can be properly adjusted to deliverymore flow and head in the system than the designer specified.

The design point can also be estimated for operation with multiplecontrolled pumps 102, with the resulting flow requirements allocatedbetween the controlled pumps 102. For example, for controlled pumps ofequivalent type or performance, the total estimated required outputproperties 114 (e.g. the maximum flow to maintain a required pressuredesign point at that location of the load) of a system or building 104may be divided equally between each controlled pump 102 to determine theindividual design points, and to account for losses or any non-linearcombined flow output. In other example embodiments, the total outputproperties (e.g. at least flow) may be divided unequally, depending onthe particular flow capacities of each control pump 102, and to accountfor losses or any non-linear combined flow output. The individual designsetpoint, as in point A (210), is thus determined for each individualcontrol pump 102.

The graph 200 includes axes which include parameters which arecorrelated. For example, flow squared is approximately proportional tohead, and flow is approximately proportional to speed. In the exampleshown, the abscissa or x-axis 204 illustrates flow in U.S. gallons perminute (GPM) and the ordinate or y-axis 206 illustrates head (H) inpounds per square inch (psi) (alternatively in feet). The range ofoperation 202 is a superimposed representation of the control pump 102with respect to those parameters, onto the graph 200.

The relationship between parameters may be approximated by particularaffinity laws, which may be affected by volume, pressure, and BrakeHorsepower (BHP). For example, for variations in impeller diameter, atconstant speed: D1/D2=Q1/Q2; H1/H2=D1²/D2²; BHP1/BHP2=D1³/D2³. Forexample, for variations in speed, with constant impeller diameter:S1/S2=Q1/Q2; H1/H2=S1²/S2²; BHP1/BHP2=S1³/S2³. Wherein: D=ImpellerDiameter (Ins/mm); H=Pump Head (Ft/m); Q=Pump Capacity (gpm/lps);S=Speed (rpm/rps); BHP=Brake Horsepower (Shaft Power—hp/kW).

Also illustrated is a best efficiency point (BEP) curve 220 of thecontrol pump 102. The partial efficiency curves are also illustrated,for example the 77% efficiency curve 238. In some example embodiments,an upper boundary of the range of operation 202 may also be furtherdefined by a motor power curve 236 (e.g. maximum horsepower). Inalternate embodiments, the boundary of the range of operation 202 mayalso be dependent on a pump speed curve 234 (shown in Hz) rather than astrict maximum motor power curve 236.

As shown in FIG. 2, one or more control curves 208 (one shown) may bedefined and programmed for an intelligent variable speed device, such asthe control pump 102. Depending on changes to the detected parameters(e.g. internal or inferred detection of changes in flow/load), theoperation of the pump device 106 may be maintained to operate on thecontrol curve 208 based on instructions from the control device 108(e.g. at a higher or lower flow point). This mode of control may also bereferred to as quadratic pressure control (QPC), as the control curve208 is a quadratic curve between two operating points (e.g., point A(210): maximum head, and point C (214): minimum head). Reference to“intelligent” devices herein includes the control pump 102 being able toself-adjust operation of the pump device 106 along the control curve208, depending on the particular required or detected load.

Other example control curves other than quadratic curves includeconstant pressure control and proportional pressure control (sometimesreferred to as straight-line control). Selection may also be made toanother specified control curve (not shown), which may be eitherpre-determined or calculated in real-time, depending on the particularapplication.

Reference is now made to FIG. 3, which shows a diagram 300 illustratinginternal sensing control (sometimes referred to as “sensorless” control)of the control pump 102 within the range of operation 202, in accordancewith example embodiments. For example, an external or proximate sensorwould not be required in such example embodiments. An internal detector304 or sensor may be used to self-detect device properties such as anamount of power and speed (P, S) of an associated motor of the pumpdevice 106. A program map 302 stored in a memory of the control device108 is used by the control device 108 to map or correlate the detectedpower and speed (P, S), to resultant output properties, such as head andflow (H, F) of the device 102, for a particular system or building 104.During operation, the control device 108 monitors the power and speed ofthe pump device 106 using the internal detector 304 and establishes theassociated head-flow condition relative to the system requirements. Theassociated head-flow (H, F) condition of the device 102 can be used tocalculate the individual contribution of the device 102 to the totaloutput properties 114 (FIG. 1) at the load. The program map 302 can beused to map the power and speed to control operation of the pump device106 onto the control curve 208, wherein a point on the control curve isused as the desired device setpoint. For example, referring to FIG. 1,as control valves 112 a, 112 b, 112 c, 112 d open or close to regulateflow to the cooling coils (e.g. load 110 a, 110 b, 110 c, 110 d), thecontrol device 108 automatically adjusts the pump speed to match therequired system pressure requirement at the current flow.

Note that the internal detector 304 for self-detecting device propertiescontrasts with some conventional existing systems which may use a localpressure sensor and flow meter which merely directly measures thepressure and flow across the control pump 102. Such variables (localpressure sensor and flow meter) may not be considered device properties,in example embodiments.

Another example embodiment of a variable speed sensorless device is acompressor which estimates refrigerant flow and lift from the electricalvariables provided by the electronic variable speed drive. In an exampleembodiment, a “sensorless” control system may be used for one or morecooling devices in a controlled system, for example as part of a“chiller plant” or other cooling system. For example, the variable speeddevice may be a cooling device including a controllable variable speedcompressor. In some example embodiments, the self-detecting deviceproperties of the cooling device may include, for example, power and/orspeed of the compressor. The resultant output properties may include,for example, variables such as temperature, humidity, flow, lift and/orpressure.

Another example embodiment of a variable speed sensorless device is afan which estimates air flow and the pressure it produces from theelectrical variables provided by the electronic variable speed drive.

Another example embodiment of a sensorless device is a belt conveyorwhich estimates its speed and the mass it carries from the electricalvariables provided by the electronic variable speed drive.

FIG. 4 illustrates an example load profile 400 for a system such as abuilding 104, for example, for a projected or measured “design day”. Theload profile 400 illustrates the operating hours percentage versus theheating/cooling load percentage. For example, as shown, many examplesystems may require operation at only 0% to 60% load capacity 90% of thetime or more. In some examples, a control pump 102 may be selected forbest efficiency operation at partial load, for example on or about 50%of peak load. Note that, ASHRAE 90.1 standard for energy savingsrequires control of devices that will result in pump motor demand of nomore than 30% of design wattage at 50% of design water flow (e.g. 70%energy savings at 50% of peak load). It is understand that the “designday” may not be limited to 24 hours, but can be determined for shorteror long system periods, such as one month, one year, or multiple years.

Referring again to FIG. 2, various points on the control curve 208 maybe selected or identified or calculated based on the load profile 400(FIG. 4), shown as point A (210), point B (212), and point C (214). Forexample, the points of the control curve 208 may be optimized forpartial load rather than 100% load. For example, referring to point B(212), at 50% flow the efficiency conforms to ASHRAE 90.1 (greater than70% energy savings). Point B (212) can be referred to as an optimalsetpoint on the control curve 208, which has maximized efficiency on thecontrol curve 208 for 50% load or the most frequent partial load. PointA (210) represents a design point which can be used for selectionpurposes for a particular system, and may represent a maximum expectedload requirement of a given system. Note that, in some exampleembodiments, there may be actually increased efficiency at part load forpoint B versus point A. Point C (214) represents a minimum flow and head(Hmin), based on 40% of the full design head, as a default, for example.Other examples may use a different value, depending on the systemrequirements. The control curve 208 may also include an illustratedthicker portion 216 which represents a typical expected load range (e.g.on or about 90%-95% of a projected load range for a projected designday). Accordingly, the range of operation 202 may be optimized forpartial load operation. In some example embodiments, the control curve208 may be re-calculated or redefined based on changes to the loadprofile 400 (FIG. 4) of the system, either automatically or manually.The curve thicker portion 216 may also change with the control curve 208based on changes to the load profile 400 (FIG. 4).

FIG. 5 illustrates an example detailed block diagram of the firstcontrol device 108 a, for controlling the first control pump 102 a (FIG.1), in accordance with an example embodiment. The first control device108 a may include one or more controllers 506 a such as a processor ormicroprocessor, which controls the overall operation of the control pump102 a. The control device 108 a may communicate with other externalcontrollers 116 or other control devices (one shown, referred to assecond control device 108 b) to co-ordinate the controlled aggregateoutput properties 114 of the control pumps 102 (FIG. 1). The controller506 a interacts with other device components such as memory 508 a,system software 512 a stored in the memory 508 a for executingapplications, input subsystems 522 a, output subsystems 520 a, and acommunications subsystem 516 a. A power source 518 a powers the controldevice 108 a. The second control device 108 b may have the same, more,or less, blocks or modules as the first control device 108 a, asappropriate. The second control device 108 b is associated with a seconddevice such as second control pump 102 b (FIG. 1).

The communications subsystem 516 a is configured to communicate with,either directly or indirectly, the other controller 116 and/or thesecond control device 108 b. The communications subsystem 516 a mayfurther be configured for wireless communication. The communicationssubsystem 516 a may be configured to communicate over a network such asa Local Area Network (LAN), wireless (Wi-Fi) network, and/or theInternet. These communications can be used to co-ordinate the operationof the control pumps 102 (FIG. 1).

The input subsystems 522 a can receive input variables. Input variablescan include, for example, the detector 304 (FIG. 3) for detecting deviceproperties such as power and speed (P, S) of the motor. Other exampleinputs may also be used. The output subsystems 520 a can control outputvariables, for example one or more operable elements of the control pump102 a. For example, the output subsystems 520 a may be configured tocontrol at least the speed of the motor of the control pump 102 a inorder to achieve a resultant desired output setpoint for head and flow(H, F), for example to operate the control pump 102 onto the controlcurve 208 (FIG. 2). Other example outputs variables, operable elements,and device properties may also be controlled.

In some example embodiments, the control device 108 a may store data inthe memory 508 a, such as correlation data 510 a. The correlation data510 a may include correlation information, for example, to correlate orinfer between the input variables and the resultant output properties.The correlation data 510 a may include, for example, the program map 302(FIG. 3) which can map the power and speed to the resultant flow andhead at the pump 102, resulting in the desired pressure setpoint at theload output. In other example embodiments, the correlation data 510 amay be in the form of a table, model, equation, calculation, inferencealgorithm, or other suitable forms.

The memory 508 a may also store other data, such as the load profile 400(FIG. 4) for the measured “design day” or average annual load. Thememory 508 a may also store other information pertinent to the system orbuilding 104 (FIG. 1).

In some example embodiments, the correlation data 510 a stores thecorrelation information for some or all of the other devices 102, suchas the second control pump 102 b (FIG. 1).

Referring still to FIG. 5, the control device 108 a includes one or moreprogram applications. In some example embodiments, the control device108 a includes a correlation application 514 a or inference application,which receives the input variables (e.g. power and speed) and determinesor infers, based from the correlation data 510 a, the resultant outputproperties (e.g. flow and head) at the pump 102 a. In some exampleembodiments, the control device 108 a includes a co-ordination module515 a, which can be configured to receive the determined individualoutput properties from the second control device 108 b, and configuredto logically co-ordinate each of the control devices 108 a, 108 b, andprovide commands or instructions to control each of the outputsubsystems 520 a, 520 b and resultant output properties in aco-ordinated manner, to achieve a specified output setpoint of theoutput properties 114.

In some example embodiments, some or all of the correlation application514 a and/or the co-ordination module 515 a may alternatively be part ofthe external controller 116.

In some example embodiments, in an example mode of operation, thecontrol device 108 a is configured to receive the input variables fromits input subsystem 522 a, and send such information as detection data(e.g. uncorrelated measured data) over the communications subsystem 516a to the other controller 116 or to the second control device 108 b, foroff-device processing which then correlates the detection data to thecorresponding output properties. The off-device processing may alsodetermine the aggregate output properties of all of the control devices108 a, 108 b, for example to output properties 114 of a common load. Thecontrol device 108 a may then receive instructions or commands throughthe communications subsystem 516 a on how to control the outputsubsystems 520 a, for example to control the local device properties oroperable elements.

In some example embodiments, in another example mode of operation, thecontrol device 108 a is configured to receive input variables of thesecond control device 108 b, either from the second control device 108 bor the other controller 116, as detection data (e.g. uncorrelatedmeasured data) through the communications system 516 a. The controldevice 108 a may also self-detect its own input variables from the inputsubsystem 522 a. The correlation application 514 a may then be used tocorrelate the detection data of all of the control devices 108 a, 108 bto their corresponding output properties. In some example embodiments,the co-ordination module 515 a may determine the aggregate outputproperties for all of the control devices 108 a, 108 b, for example tothe output properties 114 of a common load. The control device 108 a maythen send instructions or commands through the communications subsystem516 a to the other controller 116 or the second control device 108 b, onhow the second control device 108 b is to control its output subsystems,for example to control its particular local device properties. Thecontrol device 108 a may also control its own output subsystems 520 a,for example to control its own device properties to the first controlpump 102 a (FIG. 1).

In some other example embodiments, the control device 108 a first mapsthe detection data to the output properties and sends the data ascorrelated data (e.g. inferred data). Similarly, the control device 108a can be configured to receive data as correlated data (e.g. inferreddata), which has been mapped to the output properties by the secondcontrol device 108 b, rather than merely receiving the detection data.The correlated data may then be co-ordinated to control each of thecontrol devices 108 a, 108 b.

Referring again to FIG. 1, the speed of each of the control pumps 102can be controlled to achieve or maintain the inferred remote pressureconstant by achieving or maintaining H=H1+(HD−H1)*(Q/QD)̂2 (hereinafterEquation 1), wherein H is the inferred local pressure, H1 is the remotepressure setpoint, HD is the local pressure at design conditions, Q isthe inferred total flow and QD is the total flow at design conditions.In example embodiments, the number of pumps running (N) is increasedwhen H<HD*(Q/QD)̂2*(N+0.5+k) (hereinafter Equation 2), and decreased ifH>HD*(Q/QD)̂2*(N−0.5−k2) (hereinafter Equation 3), where k and k2constants to ensure a deadband around the sequencing threshold.

Reference is now made to FIG. 8, which illustrates a flow diagram of anexample method 800 for co-ordinating control of two or more controldevices, in accordance with an example embodiment. The devices eachinclude a communication subsystem and are configured to self-detect oneor more device properties, the device properties resulting in outputhaving one or more output properties. At event 802, the method 800includes detecting inputs including the one or more device properties ofeach device. At event 804, the method 800 includes correlating, for eachdevice, the detected one or more device properties to the one or moreoutput properties, at each respective device. The respective one or moreoutput properties can then be calculated to determine their individualcontributions to a system load point. At event 806, the method 800includes determining the aggregate output properties to the load fromthe individual one or more output properties. At event 808, the method800 includes comparing the determined aggregate output properties 114with a setpoint, such as a pressure setpoint at the load. For example,it may be determined that one or more of the determined aggregate outputproperties are greater than, less than, or properly maintained at thesetpoint. For example, this control may be performed using Equation 1,as detailed above. At event 810, the method includes co-ordinatingcontrol of each of the devices to operate the respective one or moredevice properties to co-ordinate the respective one or more outputproperties to achieve the setpoint. This may include increasing,decreasing, or maintaining the respective one or more device propertiesin response, for example to a point on the control curve 208 (FIG. 2).The method 800 may be repeated, for example, as indicated by thefeedback loop 812. The method 800 can be automated in that manualcontrol would not be required.

In another example embodiment, the method 800 may include a decision toturn on or turn off one or more of the control pumps 102, based onpredetermined criteria. For example, the decision may be made usingEquation 2 and Equation 3, as detailed above.

While the method 800 illustrated in FIG. 8 is represented as a feedbackloop 812, in some other example embodiments each event may representstate-based operations or modules, rather than a chronological flow.

For example, referring to FIG. 1, the various events of the method 800of FIG. 8 may be performed by the first control device 108 a, the secondcontrol device 108 b, and/or the external controller 116, either aloneor in combination.

Reference is now made to FIG. 6, which illustrates an example embodimentof a control system 600 for co-ordinating two or more sensorless controldevices (two shown), illustrated as first control device 108 a andsecond control device 108 b. Similar reference numbers are used forconvenience of reference. As shown, each control device 108 a, 108 b mayeach respectively include the controller 506 a, 506 b, the inputsubsystem 522 a, 522 b, and the output subsystem 520 a, 520 b forexample to control at least one or more operable device members (notshown).

A co-ordination module 602 is shown, which may either be part of atleast one of the control devices 108 a, 108 b, or a separate externaldevice such as the controller 116 (FIG. 1). Similarly, the inferenceapplication 514 a, 514 b may either be part of at least one of thecontrol devices 108 a, 108 b, or part of a separate device such as thecontroller 116 (FIG. 1).

In operation, the co-ordination module 602 co-ordinates the controldevices 108 a, 108 b to produce a co-ordinated output(s). In the exampleembodiment shown, the control devices 108 a, 108 b work in parallel tosatisfy a certain demand or shared load 114, and which infer the valueof one or more of each device output(s) properties by indirectlyinferring them from other measured input variables and/or deviceproperties. This co-ordination is achieved by using the inferenceapplication 514 a, 514 b which receives the measured inputs, tocalculate or infer the corresponding individual output properties ateach device 102 (e.g. head and flow at each device). From thoseindividual output properties, the individual contribution from eachdevice 102 to the load (individually to output properties 114) can becalculated based on the system/building setup. From those individualcontributions, the co-ordination module 602 estimates one or moreproperties of the aggregate or combined output properties 114 at thesystem load of all the control devices 108 a, 108 b. The co-ordinationmodule 602 compares with a setpoint of the combined output properties(typically a pressure variable), and then determines how the operableelements of each control device 108 a, 108 b should be controlled and atwhat intensity.

It would be appreciated that the aggregate or combined output properties114 may be calculated as a linear combination or a non-linearcombination of the individual output properties, depending on theparticular property being calculated, and to account for losses in thesystem, as appropriate.

In some example embodiments, when the co-ordination module 602 is partof the first control device 108 a, this may be considered a master-slaveconfiguration, wherein the first control device 108 a is the masterdevice and the second control device 108 b is the slave device. Inanother example embodiment, the co-ordination module 602 is embedded inmore of the control devices 108 a, 108 b than actually required, forfail safe redundancy.

Referring still to FIG. 6, some particular example controlleddistributions to the output subsystems 520 a, 520 b will now bedescribed in greater detail. In one example embodiment, for example whenthe output subsystems 520 a, 520 b are associated with controllingdevice properties of equivalent type or performance, the deviceproperties of each control pump 102 may be controlled to have equaldevice properties to distribute the flow load requirements. In otherexample embodiments, there may be unequal distribution, for example thefirst control pump 102 a may have a higher flow capacity than the secondcontrol pump 102 b (FIG. 1). In another example embodiment, each controlpump 102 may be controlled so as to best optimize the efficiency of therespective control pumps 102 at partial load, for example to maintaintheir respective control curves 208 (FIG. 2) or to best approach Point B(212) on the respective control curve 208.

Referring still to FIG. 6, in an optimal system running condition, eachof the control devices 108 a, 108 b are controlled by the co-ordinationmodule 602 to operate on their respective control curves 208 (FIG. 2) tomaintain the pressure setpoint at the output properties 114. This alsoallows each control pump 102 to be optimized for partial load operation.For example, as an initial allocation, each of the control pumps 102 maybe given a percentage flow allocation (e.g. can be 50% split betweeneach control device 108 a, 108 b in this example), to determine orcalculate the required initial setpoint (e.g. Point A (210), FIG. 2).The percentage responsibility of required flow for each control pump 102can then be determined by dividing the percentage flow allocation fromthe inferred total output properties 114. Each of the control pumps 102can then be controlled along their control curves 208 to increase ordecrease operation of the motor or other operable element, to achievethe percentage responsibility per required flow.

However, if one of the control pumps (e.g. first control pump 102 a) isdetermined to be underperforming or off of its control curve 208, theco-ordination module 602 may first attempt to control the first controlpump 102 a to operate onto its control curve 208. However, if this isnot possible (e.g. damaged, underperforming, would result in outside ofoperation range 202, otherwise too far off control curve 208, etc.), theremaining control pumps (e.g. 102 b) may be controlled to increase theirdevice properties on their respective control curves 208 in order toachieve the pressure setpoint at the required flow at the outputproperties 114, to compensate for at least some of the deficiencies ofthe first control pump 102 a. Similarly, one of the control pumps 102may be intentionally disabled (e.g. maintenance, inspection, saveoperating costs, night-time conservation, etc.), with the remainingcontrol pumps 102 being controlled accordingly.

In other example embodiments, the distribution between the outputsubsystems 520 a, 520 b may be dynamically adjusted over time so as totrack and suitably distribute wear as between the control pumps 102.

Reference is now made to FIG. 7, which illustrates another exampleembodiment of a control system 700 for co-ordinating two or moresensorless control devices (two shown), illustrated as first controldevice 108 a and second control device 108 b. Similar reference numbersare used for convenience of reference. This may be referred to as apeer-to-peer system, in some example embodiments. An external controller116 may not be required in such example embodiments. In the exampleshown, each of the first control device 108 a and second control device108 b may control their own output subsystems 520 a, 520 b, so as toachieve a co-ordinated combined system output 114. As shown, eachco-ordination module 515 a, 515 b is configured to each take intoaccount the inferred and/or measured values from both of the inputsubsystems 522 a, 522 b. For example, as shown, the first co-ordinationmodule 515 a may estimate one or more output properties of the combinedoutput properties 114 from the individual inferred and/or measuredvalues.

As shown, the first co-ordination module 515 a receives the inferredand/or measured values and calculates the individual output propertiesof each device 102 (e.g. head and flow). From those individual outputproperties, the individual contribution from each device 102 to the load(individually at output properties 114) can be calculated based on thesystem/building setup. The first co-ordination module 515 a can thencalculate or infer the aggregate output properties 114 at the load.

The first co-ordination module 515 a then compares the inferredaggregate output properties 114 with a setpoint of the output properties(typically a pressure variable setpoint), and then determines theindividual allocation contribution required by the first outputsubsystem 520 a (e.g. calculating 50% of the total required contributionin this example). The first output subsystem 520 a is then controlledand at a controlled intensity (e.g. increase, decrease, or maintain thespeed of the motor, or other device properties), with the resultantco-ordinated output properties being again inferred by furthermeasurements at the input subsystem 522 a, 522 b.

As shown in FIG. 7, the second co-ordination module 515 b may besimilarly configured as the first co-ordination module 515 a, toconsider both input subsystem 522 a, 522 b to control the second outputsubsystem 520 b. For example, each of the control pumps 102 may beinitially given a percentage flow allocation. Each of the control pumps102 can then be controlled along their control curves 208 to increase ordecrease operation of the motor or other operable element, based on theaggregate load output properties 114. The aggregate load outputproperties 114 may be used to calculate per control pump 102, therequire flow and corresponding motor speed (e.g. to maintain thepercentage flow, e.g. 50% for each output subsystem 520 a, 520 b in thisexample). Accordingly, both of the co-ordination modules 515 a, 515 boperate together to co-ordinate their respective output subsystems 520a, 520 b to achieve the selected output setpoint at the load outputproperties 114.

As shown in FIG. 7, note that in some example embodiments each of theco-ordination modules 515 a, 515 b are not necessarily in communicationwith each other in order to functionally operate in co-ordination. Inother example embodiments, not shown, the co-ordination modules 515 a,515 b are in communication with each other for additional co-ordinationthere between.

Although example embodiments have been primarily described with respectto the control devices being arranged in parallel, it would beappreciated that other arrangements may be implemented. For example, insome example embodiments the controlled devices can be arranged inseries, for example for a pipeline, booster, or other such application.The resultant output properties are still co-ordinated in such exampleembodiments. For example, the output setpoint and output properties forthe load may be the located at the end of the series. The control of theoutput subsystems, device properties, and operable elements are stillperformed in a co-ordinated manner in such example embodiments. In someexample embodiments the control devices can be arranged in a combinationof series and parallel.

Reference is now made to FIG. 9, which illustrates an example operationgraph 900 of head versus flow for a variable speed control pump 102(FIG. 1), in accordance with an example embodiment. Generally, theoperation graph 900 illustrates an adjustable control curve 902 which isused to optimize a system hydraulic resistance (K=H/Q²) of e.g. thecirculating system 100 of FIG. 1. System hydraulic resistance is alsoreferred to as hydraulic conductivity.

Referring therefore to FIG. 1, one or more controllers such as controldevice 108 and/or external controller 116 may be used to dynamicallydetermine or calculate the control curve 902 (FIG. 9) in real-timeduring runtime operation of the circulating system 100. Generally, thecontroller automatically update or adjust the model or parameters of thecontrol pump 102, to adjust the control curve 902 (FIG. 9) to compensatefor flow loss or other changes which may occur in conditions of thesystem 100. The controller is self-learning in that at least some of theinitial and subsequent parameters of the system 100 are determinedautomatically, i.e., would not require manual configuration. The controlpump 102 is controlled using data collected during runtime. The controlpump 102 is controlled in order to reduce pump energy consumptionwithout compromising system stability or starving the load(s) 110 a, 110b, 110 c, 110 d.

In some example embodiments, the control pumps 102 can be sensorless inthe sense that they can be used to determine or calculate the systemresistance without an external sensor. This is performed by having thecontrol pump 102 self-detect its own device properties such as power andspeed, and inferring or correlating the resultant head and flow, asdescribed in detail above with respect to FIG. 3. The present systemresistance can then be calculated as K=H/Q².

Still referring to FIG. 1, the control pump 102 can distribute a hot orchilled fluid to one or more loads 110 a, 110 b, 110 c, 110 d, whichcontrol the flow they take using modulating valves 112 a, 112 b, 112 c,112 d, or in some example embodiments there are sufficient loads withon/off valves that the system 100 can be treated as modulating. As shownin FIG. 9, the pump speed can be set at any value between a minimumspeed 904 and a maximum speed 906 which depends on the pump-motor-driveset. In the example shown in FIG. 9, the system design point 908represents the “design” flow and head of the system 100, which may beinitially unknown and may change over time. It is presumed that thesystem design point 908 is lower or equal to the pump best efficiencypoint, BEP 910, for flow and head, based on suitable pump selection. Inoperation, the pump speed is adjusted using a flow loss compensationalgorithm with a quadratic control curve: Head=A+B×Flow², as shown.Higher order polynomials may also be used, in other example embodiments.In some example embodiments, it can be presumed that the system load isno more than 40% asymmetrical; that is, at any time the maximum percentflow demand from a load cannot be more than 40% higher than that of theless demanding load. In some example embodiments, it may also bepresumed that the valves 112 a, 112 b, 112 c, 112 d have approximatelyequal percentage curves.

Referring again to FIG. 9, operation using a single control pump 102will be described for ease of illustration, although it can beappreciated that more than one control pump 102 may be operated withinthe system 100. Generally, the example embodiment of FIG. 9 operates tokeep the valves 112 a, 112 b, 112 c, 112 d as open as possible, in orderto minimize the kinetic (pump) energy dissipated by them. This isperformed in a controlled manner, to prevent the system from not beingable to provide enough flow when the valves 112 a, 112 b, 112 c, 112 dare full open.

For example, the control pump 102 can be controlled to slowly adjust thecontrol curve 902 such that the valves will operate most of the timebetween 60% and 90% open, and half of the time on each side of 75% open.The average valve opening is detected by calculating the average systemresistance K=H/Q². An invalid zone 918 represents a right boundaryoutside of the range of operation of the control pump 102. Otherboundaries may be provided or defined for the range of operation of thecontrol pump 102.

The following relationship was established by analyzing different valvebrands curves (KFO is the resistance when the valve is full open):

Position (%) K/KFO 40 44 60 15 75 6.5 90 2 100 1

The value of K is monitored and the following four situations cause thecontrol curve parameters (A and B) to be adjusted: 1) valves are tooopen (K<2 KFO): right side of the curve is raised; 2) valves are tooclosed (K>15KFO): left side of the curve is lowered; 3) valves are mostof the time open less than 75%: the curve is lowered; 4) valves are mostof the time open more than 75%: the curve is raised. For items 3) or 4),other suitable percentage values can range from 50% to 100%.

Reference is now made to FIGS. 10A, 10B and 10C, which illustrateexample flow diagrams for adjusting the control curve 902 of FIG. 9, inaccordance with example embodiments. As shown, these algorithms arereferred to as valve distribution process 1000 (FIG. 10A), valveposition process 1002 (FIG. 10B), and resistance review process 1004(FIG. 10C), respectively. In example embodiments, some or all of theprocesses 1000, 1002, 1004 may be performed simultaneously duringruntime operation of the control pump 102 on the system 100. In someexample embodiments, the processes 1000, 1002, 1004 can be performedduring initial setup of the system 100 as well as during operation.

Initially, with reference to the control curve 902 of FIG. 9, thefollowing parameters can be initialized, which initially references theBEP 910 for the initial system resistance (valves full open):

A=Z×BEP_Head, (Z=0-10);

B=(BEP_Head−A)/BEP_Flow²; and

C=BEP_Head/BEP_Flow² (when all valves full open).

The various system resistance curves are shown on the graph 900, forexample K=15C (912), K=6.5C (914), and K=2C (916). The system designpoint 908 and control curve 902 can be dynamically determined in realtime, without having special knowledge of the system resistance. Thesystem resistance can change due to flow losses and other factors. Asmentioned, some or all of the processes 1000, 1002, 1004 may beperformed simultaneously to adjust the control curve 902.

Referring to FIG. 10A, the valve distribution process 1000 determineswhether the valves are most of the time open less than 75%, and thecurve is lowered in response. The valve distribution process 1000 alsodetermines whether the valves are most of the time open more than 75%,and the curve is raised in response.

At event 1010, calculate or infer K=H/Q² and count the time K is greaterthan 6.5C (Count_1) and the time K is less than 6.5C (Count_2). As inthe above table, recall that 6.5C corresponds to the valves being 75%open.

At event 1012, it is determined whether 24 hours has passed for countingthe times for K, e.g. if Count_1+Count_2>24 hours (the pump has beenrunning more than 24 hours since the last check). If 24 hours haspassed, then at event 1014: if Count_1>Count_2+4 hs then decrease A by1%; if Count_1+4 hs<Count_2 then increase A by 1%. Otherwise, A ismaintained. At event 1014, reset Count_1 to 0 and Count_2 to 0. Themethod 1000 then repeats to step 1010 for the next 24 hour interval.

Referring now to FIG. 10B, the valve position process 1002 determineswhether the valves are too open (K<2 KFO), and the right side of thecurve is raised in response. The valve position process 1002 alsodetermines whether the valves are too closed (K>15KFO), and the leftside of the curve is lowered in response.

At event 1020, calculate K=H/Q². At event 1022, when K stays above 15C,every 30 minutes decrease A by 5% and increase B by 5%. At event 1024,when K stays below 2C, every 30 minutes decrease A by 5% and increase Bby 5%. The method 1002 then repeats to event 1020.

Referring to FIG. 10C the resistance review process 1004 is used toperiodically determine or review the minimum system resistance, when thevalves are fully open. At event 1034, the minimum value of K averagedover 1 min achieved (D) is determined and stored. At event 1036, at anytime if D<C, replace C with D.

At event 1038, after the first 2 days of operation (e.g. after theinitial setup), C is replaced with D (event 1040). At event 1042, D isreset to zero. At event 1044, after the initial setup interval,different “review intervals” may be used. For example, review intervalscan be given by the following: 1) first interval is 2 days after theinitial 2 days of operation; 2) second interval is 4 days thereafter; 3)third interval is 8 days therafter; 4) fourth interval is 16 daysthereafter; each subsequent interval is 16 days thereafter for theindefinite runtime duration of the system. Other suitable intervals canrange from 1 to 30 days.

After every “review interval” is completed (event 1044), at event 1046,if K≦3C, reduce speed to the minimum pump speed (e.g. default 30%) for15 minutes. This essentially forces the valves to be fully open. Notethat, event 1036 will trigger if D<C at this stage, such that C isreplaced with D. At event 1048, reset D to zero and then loop to start anew review interval at event 1044.

Note that, the example embodiments of FIGS. 10A to 10C may further belimited by the range of operation of the operation graph 900 (FIG. 9).For example, the control curve 902 cannot be adjusted using thosemethods to fall outside of the range of operation. Any values or rangesprovided are intended be illustrative, and can be on or about thosevalues or ranges, or other suitable values or ranges.

Reference is now made to FIG. 11, in the context of FIG. 2, whichillustrates optimizing of pump efficiency in accordance with an exampleembodiment. With reference to FIG. 2, the control curve 202 may beadjusted or controlled in real-time in dependence of a detected(measured or inferred) load of the system 100. Typically, the load flowof the system 100 is tracked in real-time to dynamically update a loadprofile 1100.

As an initial conceptual matter, the load profile 1100 of FIG. 11 may beimplemented as a graphical user interface (GUI) screen 1100 forconfiguring the load profile 1102 of the building 104. The load profile1102 is normalized to one (100%) in this example representation. Theload profile 1102 represents a projected or measured percentage flow1104 for specified time periods 1106, with the percentage flow beingacross e.g. a “design day”. The interface screen 1100 is initiallypresented with a default load profile 1102, as shown. A buildingdesigner (user) may wish to configure the load profile to the particularbuilding 104 to something other than the default load profile. As shown,in some example embodiments, the user may select particular samplingpoints 1108 of the load profile 1102 on the interface screen 1100, anddrag those points 1108 to different flow 1104 and time periods 1106, inorder to adjust the default load profile to the desired particularprojected or measured flow profile of the actual system or building 104.In other example embodiments, the building designer may input specificflow 1104 and time periods 1106 for the particular points 1108 byinputting into a field-based interface (not shown), or by uploading asuitably configured file which provides these values. In other exampleembodiments, the axes of the load profile 1102 instead may be equivalentto those shown in FIG. 4.

An automated system for updating the load profile 1102 will now bedescribed, rather than the just-described manual user interface. Theload profile 1102 may be an initial default load profile. With referencenow to FIGS. 1 and 2, one or more controllers such as control device 108and/or external controller 116 may be used to dynamically determine orcalculate the control curve 208 in real-time during operation.Generally, the controller automatically adjust the model or parametersof the control pump 102, to adjust the control curve 208 to compensatefor changes in the design day or load profile 1102. The control pump 102is controlled using data collected during run time. The control pump 102is controlled in order to optimize pump efficiency without compromisingsystem stability and to maintain compliance with ASHRAE 90.1.

For the control curve 208, with reference again to FIG. 2, theillustrated thicker portion 216 may be dynamically adjusted withreference to the updated load profile 1102 (FIG. 11). The control curve208 can also be dynamically updated in dependence of the updated loadprofile 1102. The intelligent variable speed device would operate alongthe dynamically changing control curve 208, which has been updated inreal time during runtime.

For example, point A (210), point B (212), and point C (214) would beupdated accordingly depending on the detected or inferred load profile1102. For example, the control curve 208 may be updated so that the mostfrequent or average load represented as point B (212), is as close tothe BEP curve 220 as possible. Although point B (212) may be initially50% of peak load, it may be dynamically determined (measured orinferred) that the load profile 1102 is asymmetric or has some otherpeak load. In response, the control curve 208 may involve adjusting orre-calculating point A (210) and/or point C (214), e.g. from the initialdefault settings. In an example embodiment, if it is determined thatpoint B (212) is to the left of the BEP curve 220, in response point A(210) is moved to the right a specified amount (e.g. 1-10%) everyspecified interval (e.g. 1 to 365 days). If it is determined that pointB (212) is to the right of the BEP curve 220, in response point A (210)is moved to the left a specified amount (e.g. 1-10%) every specifiedinterval. In an example embodiment, if it is determined that point B(212) is on top of the BEP curve 220, in response point A (210) and/orpoint C (214) are moved downwardly a specified amount (e.g. 1-10%) everyspecified interval. If it is determined that point B (212) is under theBEP curve 220, in response point A (210) and/or point C (214) are movedupwardly a specified amount (e.g. 1-10%) every specified interval.

In some example embodiments, the control pumps 102 are sensorless inthat they can be used to determine or calculate the required flow loadwithout an external sensor. This is performed by having the control pump102 self-detect the device properties such as power and speed, andinferring or correlating the resultant head and flow, as described indetail above with respect to FIG. 3.

FIG. 12 illustrates an example block diagram of a circulating system1200 having external sensors, in accordance with another exampleembodiment. Similar references numerals as FIG. 1 are used forconvenience of reference. Although the above exemplary embodiments ofFIGS. 9, 10A, 10B, 10C and 11 have been primarily described in thecontext of sensorless devices, in some other example embodiments it maybe appropriate to use external sensors. The system 1200 includes anexternal sensor 1202 which can be used to detect, for example, thepressure and flow. Another sensor 1204 can be used to detect, forexample, the head and flow output from the device 102. A controller 1206may be in communication one or both of the sensors 1202, 1204 in orderto receive and track the sensor measurements, and control operation ofthe control pump(s) 102. Accordingly, any calculation in the embodimentsdescribed with respect to FIGS. 9 to 11 which require correlating orinferring a pressure or head from the device properties can instead bedetermined using information measured by one or both of the sensors1202, 1204. For example, the embodiments illustrated in FIGS. 9, 10A,10B, 10C and 11 may be configured with external sensors, depending onthe particular application.

FIG. 13 illustrates an example control system 1300 for controlling anoperable system 1302, in accordance with an example embodiment.Generally, in the control system 1300, outputs 1310 and inputs includingoptimizable inputs 1304 are measured and an estimation method 1306 oralgorithm is updated or adjusted for the system 1302. In some exampleembodiments, the control system 1300 includes continuous feedbackloop(s) which operate during initial setup as well as indefinite runtimeof the system 1302 (continuously or at discrete times). In some exampleembodiments, no or little prior knowledge of the system 1302 isrequired. Rather, the control system 1300 controls and adapts itsperformance and control models based on self-learning of the system1302. In some example embodiments, the system 1302 can be e.g. thecirculating system 100 illustrated in FIG. 1, or the circulating system1200 illustrated in FIG. 12.

The system 1302 produces certain output(s) 1310 characterized by one ofmore variables (e.g. flow, temperature, viscosity, thickness, speed,thermal energy, items per minute, distance, etc), composed of severalparts whose operation points/path can be characterized by a finitenumber of continuous or discrete variables (e.g. speed, temperature,power, run status, rpm, mode of operation, gear, breaks position, etc).

These continuous or discrete variables work together to produce theoutput(s) 1310 of the system 1302 and interact in such a way that theoperation point/path of one output variable determines or restricts theoperation points of the other output variables. There may also berestrictions to the operation of each part, i.e., limited range(s) forthe values its operation point characterizing variable(s) can take.These continuous or discrete variables variable(s) may include deviceproperties of controllable operable element(s), e.g. a pump motor.

The system 1302 includes input variable(s), which may includenon-controllable variable(s) 1314 which are externally determined andcannot be controlled (e.g. outdoor temperature, commodities prices,output demand, etc), that affect the operation of the system parts orshould be taken into account when deciding how to operate the system1302 efficiently. The system 1302 includes input variables such asoptimizable input(s) 1304 which can be optimized. Example optimizableinput(s) 1304 may be consumable inputs, e.g., energy, chemicals, water,money or time. Other input variables 1324 may also be input into thesystem 1302. As shown, the input variables can be measured usingmeasurement 1308 in order to adjust a parameter of, determine, orcalculate the appropriate model by the model adjust module 1320. Variousinput variables can include consumable inputs (energy, chemicals, etc)or other inputs (outdoor temperature, demand, speed, line voltage, etc).

In the system 1302, there is more than one operation point or path thatcan give a desired output 1310. The control system 1300 is configured toproduce the required output 1310 (to satisfy the output demand)optimizing the use of one or more of the optimizable inputs 1304required to produce that output 1310.

In some example embodiments, there is provided a method or model foreach part of the system 1302, such as e.g. formula(s), table(s), oralgorithm, to predict the amount the system 1302 uses the optimizableinputs 1304, for all the points of operation in its allowed range. Anoptimum point/path 1312 is then determined and updated by the estimationmethod 1306.

The system operation point or system status 1322 is given by all of thecharacterizing variables of the system parts, reduced by therestrictions imposed by the interaction or interconnection of thevariables, and limited in range by the parts operational restrictions.

For each system allowed operation point, the amount of optimizableinputs 1304 the system 1302 would consume can be calculated as the sumof the amounts consumed by each of its parts. The system controllablevariables are its characterizing variables minus those externallydetermined non-controllable variable(s) 1314.

As shown in FIG. 13, in example embodiments, given the non-controllablevariable(s) 1314 (the conditions in which the system has to work), theoptimization module 1316 uses the estimation method 1306 to find anoptimum point or path 1312 compatible with the given conditions, thenthe system 1302 is commanded by the controller module 1318 to operate atthat point or follow that path.

The use of input variables including the optimizable input(s) 1304 ismeasured and the estimation method 1306 is updated using the modeladjust module 1320 to make its prediction for the reported system status1322 closer to the use or consumption measurement 1308 of theoptimizable inputs 1304.

Note that the optimization module 1316, controller 1318 and measurementmodule 1308 can reside in one or more devices, or be embedded in thesystem 1302, leading to different example embodiments. In some exampleembodiment, the optimization method 1316 can be executed upfront, by amicroprocessor device. A particular model or method can then besubsequently selected from a set of predetermined models or methodswhich best optimizes the optimum point/path 1312.

Accordingly, the control system 1300 controls the system 1302, toproduce the desired output(s) 1310 while optimizing the use of one ormore optimizable input(s) 1304 by dynamically determining anoptimization method 1316 to predict the amount of the optimizableinput(s) 1304 used at each possible operation point or path (e.g.operation trajectory in time) that produces the desired output(s) 1310,then finding the optimal point/path 1312, and finally commanding thecontrollable variables 1304 to achieve said optimal point or trajectory1312.

In some example embodiments, rather than through the measurements 1308,the use of the optimizable inputs is estimated using explicit analyticalformulas. In some example embodiments, the system's optimizable inputsuse is estimated using numerical tables.

In some example embodiments, the optimizable inputs estimation module1306 or formulae is simple enough that they allow solving analyticallythe optimization and obtaining explicit formulas, parametric in theoutput(s) 1310 and non-controllable variables 1314, to command thecontrollable variables 1304.

In some example embodiments, the optimization module 1316 is numericallysolved upfront, thus resulting in numerical table(s) and/or explicitformulas to command the controllable variables 1304.

In some example embodiments, the optimization module 1316 is performedby a microprocessor based device executing software while the system isrunning, and for the particular non-controllable conditions theoptimization module 1316 is encountering.

In some example embodiments, the estimation module 1306 or formulas havetuning parameters and these and/or the values in the table(s) areperiodically adjusted based on the actual use of optimizable inputsmeasured. A system test can be implemented at specified times toeliminate some variables to increase the accuracy of the estimationmodule 1306.

Variations may be made in example embodiments of the present disclosure.Some example embodiments may be applied to any variable speed device,and not limited to variable speed control pumps. For example, someadditional embodiments may use different parameters or variables, andmay use more than two parameters (e.g. three parameters on a threedimensional graph). For example, the speed (rpm) is also illustrated onthe described control curves. Further, temperature (Fahrenheit) versustemperature load (BTU/hr) may be parameters or variables which areconsidered for control curves, for example for variable temperaturecontrol which can be controlled by a variable speed circulating fan.Some example embodiments may be applied to any devices which aredependent on two or more correlated parameters. Some example embodimentscan include variables dependent on parameters or variables such asliquid, temperature, viscosity, suction pressure, site elevation andnumber of pump operating.

In example embodiments, as appropriate, each illustrated block or modulemay represent software, hardware, or a combination of hardware andsoftware. Further, some of the blocks or modules may be combined inother example embodiments, and more or less blocks or modules may bepresent in other example embodiments. Furthermore, some of the blocks ormodules may be separated into a number of sub-blocks or sub-modules inother embodiments.

While some of the present embodiments are described in terms of methods,a person of ordinary skill in the art will understand that presentembodiments are also directed to various apparatus such as a serverapparatus including components for performing at least some of theaspects and features of the described methods, be it by way of hardwarecomponents, software or any combination of the two, or in any othermanner. Moreover, an article of manufacture for use with the apparatus,such as a pre-recorded storage device or other similar non-transitorycomputer readable medium including program instructions recordedthereon, or a computer data signal carrying computer readable programinstructions may direct an apparatus to facilitate the practice of thedescribed methods. It is understood that such apparatus, articles ofmanufacture, and computer data signals also come within the scope of thepresent example embodiments.

While some of the above examples have been described as occurring in aparticular order, it will be appreciated to persons skilled in the artthat some of the messages or steps or processes may be performed in adifferent order provided that the result of the changed order of anygiven step will not prevent or impair the occurrence of subsequentsteps. Furthermore, some of the messages or steps described above may beremoved or combined in other embodiments, and some of the messages orsteps described above may be separated into a number of sub-messages orsub-steps in other embodiments. Even further, some or all of the stepsof the conversations may be repeated, as necessary. Elements describedas methods or steps similarly apply to systems or subcomponents, andvice-versa.

The term “computer readable medium” as used herein includes any mediumwhich can store instructions, program steps, or the like, for use by orexecution by a computer or other computing device including, but notlimited to: magnetic media, such as a diskette, a disk drive, a magneticdrum, a magneto-optical disk, a magnetic tape, a magnetic core memory,or the like; electronic storage, such as a random access memory (RAM) ofany type including static RAM, dynamic RAM, synchronous dynamic RAM(SDRAM), a read-only memory (ROM), a programmable-read-only memory ofany type including PROM, EPROM, EEPROM, FLASH, EAROM, a so-called “solidstate disk”, other electronic storage of any type including acharge-coupled device (CCD), or magnetic bubble memory, a portableelectronic data-carrying card of any type including COMPACT FLASH,SECURE DIGITAL (SD-CARD), MEMORY STICK, and the like; and optical mediasuch as a Compact Disc (CD), Digital Versatile Disc (DVD) or BLU-RAYDisc.

Variations may be made to some example embodiments, which may includecombinations and sub-combinations of any of the above. The variousembodiments presented above are merely examples and are in no way meantto limit the scope of this disclosure. Variations of the innovationsdescribed herein will be apparent to persons of ordinary skill in theart having the benefit of the present disclosure, such variations beingwithin the intended scope of the present disclosure. In particular,features from one or more of the above-described embodiments may beselected to create alternative embodiments comprised of asub-combination of features which may not be explicitly described above.In addition, features from one or more of the above-describedembodiments may be selected and combined to create alternativeembodiments comprised of a combination of features which may not beexplicitly described above. Features suitable for such combinations andsub-combinations would be readily apparent to persons skilled in the artupon review of the present disclosure as a whole. The subject matterdescribed herein intends to cover and embrace all suitable changes intechnology.

1. A control system for controlling an operable flow system, comprising:one or more operable elements resulting in output variables, at leastone of the operable elements including a respective variablycontrollable motor, wherein there is more than one operation point orpath of system variables of the operable flow system that can provide agiven output setpoint of a circulating medium, wherein at least onesystem variable at an operation point or path restricts operation ofanother system variable at the operation point or path; and one or morecontrollers configured to operate in a control loop to: detect inputvariables, the input variables including non-controllable variables andsystem controllable variables, the non-controllable variables includingoutput demand, the system controllable variables include a speed of atleast one of the variably controllable motors and at least oneoptimizable input variable, the at least one optimizable input variableincluding power consumed, detect the system variables including pressureand flow of the circulating medium for the operable flow system, updatea model with respect to the at least one optimizable input variable,comprising calculating the updated model using established relationshipsbetween variables, the detected input variables and the detected systemvariables, the updated model providing, based on establishedrelationships between variables, prediction of use of the inputvariables in all possible operation points or paths of the systemvariables, including the pressure and the flow, which achieve an outputsetpoint of the circulating medium, and operate, based on one or more ofthe detected input variables and the detected system variables, the oneor more operable elements in accordance with the updated model toprovide an optimal operation point or path of the system variables whichachieves the output setpoint and which optimizes consumption of the atleast one optimizable input variable; wherein for iterations of thecontrol loop said updating of the model is based on said operating ofthe one or more operable elements during the control loop.
 2. Thecontrol system as claimed in claim 1, wherein the control loop isperformed during initial setup and subsequent operation of the one ormore operable elements in the operable flow system.
 3. The controlsystem as claimed in claim 1, wherein a non controllable input variableincludes a variable system hydraulic resistance of the operable flowsystem.
 4. The control system as claimed in claim 1, wherein the one ormore controllers are further configured to perform a system reviewthrough specified operation of the output variables to calibrate atleast one optimizable input variable.
 5. The control system as claimedin claim 4, wherein during the system review the one or more controllersare further configured to determine a minimum system hydraulicresistance as one of the system variables by starving the operable flowsystem.
 6. The control system as claimed in claim 1, wherein saidupdating includes updating the model for subsequent iterations of thecontrol loop.
 7. The control system as claimed in claim 1, wherein theoptimizable input variable comprises a power efficiency variable of theone or more operable elements.
 8. The control system as claimed in claim1, wherein said detecting of the output variables comprisesself-detecting device properties of the operable element and correlatingto the output variables.
 9. The control system as claimed in claim 1,wherein said optimizing includes maintaining a specified average valueof the at least one optimizable input variable.
 10. The control systemas claimed in claim 1, wherein said optimizing includes maintaining aspecified operation range of the at least one optimizable inputvariable.
 11. The control system as claimed in claim 1, wherein saidoptimizing includes maintaining a specified distribution, detected overa specified operation time, of the at least one optimizable inputvariable.
 12. The control system as claimed in claim 1, wherein at leastone optimizable input variable is a consumable input variable.
 13. Thecontrol system as claimed in claim 1, wherein detecting of the systemvariables further includes correlating at least one of the systemvariables from at least one self-detected device property of the one ormore operable elements.
 14. The control system as claimed in claim 1:wherein the operable flow system further comprises a chilled circulatingsystem including: a refrigerant, and wherein the one or more operableelements includes a compressor having the respective variablycontrollable motor for controlling circulation of the refrigerant,resulting in the output variables including lift and flow for therefrigerant.
 15. The control system as claimed in claim 1, wherein theoutput variables include a temperature variable to achieve the outputsetpoint.
 16. The control system as claimed in claim 1, wherein thenon-controllable variables include outdoor temperature.
 17. A method forcontrolling an operable flow system, the operable flow system includingone or more operable elements resulting in output variables, at leastone of the operable elements including a respective variablycontrollable motor, wherein there is more than one operation point orpath of system variables of the operable flow system that can provide agiven output setpoint of a circulating medium, wherein at least onesystem variable at an operation point or path restricts operation ofanother system variable at the operation point or path, the method beingperformed as a control loop and comprising: detecting input variables,the input variables including non-controllable variables and systemcontrollable variables, the non-controllable variables including outputdemand, the system controllable variables include a speed of at leastone of the variably controllable motors and at least one optimizableinput variable, the at least one optimizable input variable includingpower consumed; detecting the system variables including pressure andflow of the circulating medium for the operable flow system; updating amodel with respect to the at least one optimizable input variable,comprising calculating the updated model using established relationshipsbetween variables, the detected input variables and the detected systemvariables, the updated model providing, based on establishedrelationships between variables, prediction of use of the inputvariables in all possible operation points or paths of the systemvariables which achieve an output setpoint; and operating, based on oneor more of the detected input variables and the detected systemvariables, the one or more operable elements in accordance with theupdated model to provide an optimal operation point or path of thesystem variables which achieves the output setpoint and which optimizesconsumption of the at least optimizable one input variable; wherein foriterations of the control loop said updating of the model is based onsaid operating of the one or more operable elements during the controlloop.
 18. A non-transitory computer readable medium comprisinginstructions which, when executed by one or more controllers, cause thecontrollers to control an operable flow system in a control loop, theoperable system including one or more operable elements resulting inoutput variables, at least one of the operable elements including arespective variably controllable motor, wherein there is more than oneoperation point or path of system variables of the operable flow systemthat can provide a given output setpoint of a circulating medium,wherein at least one system variable at an operation point or pathrestricts operation of another system variable at the operation point orpath, the instructions comprising: instructions for detecting inputvariables, the input variables including non-controllable variables andsystem controllable variables, the non-controllable variables includingoutput demand, the system controllable variables include a speed of atleast one of the variably controllable motors and at least oneoptimizable input variable, the at least one optimizable input variableincluding power consumed; instructions for detecting the systemvariables including pressure and flow of the circulating medium for theoperable flow system; instructions for updating a model with respect tothe at least one optimizable input variable, comprising calculating theupdated model using established relationships between variables, thedetected input variables and the detected system variables, the updatedmodel providing, based on established relationships between variables,prediction of use of the input variables in all possible operationpoints or paths of the system variables which achieve an output setpointof the circulating medium; and instructions for operating, based on oneor more of the detected input variables and the detected systemvariables, the one or more operable elements in accordance with theupdated model to provide an optimal operation point or path of thesystem variables which achieves the output setpoint and which optimizesconsumption of the at least one optimizable input variable; wherein foriterations of the control loop said updating of the model is based onsaid operating of the one or more operable elements during the controlloop.